AI and bioprinting accelerate tissue engineering

According to the University of Maryland (UMD), researchers at the A. James Clark School of Engineering are developing artificial intelligence systems to improve 3D bioprinting. The goal is to move toward a future where replacement tissues and organs can be produced on demand, removing the need for donors.

Bioprinting involves printing with materials that contain living cells and nutrients that keep those cells viable. The long-term ambition is to print everything from skin and bone to complex organs such as hearts and kidneys, enabling fully functional transplants.

The UMD team is currently exploring in situ bioprinting, in which new tissue could be printed directly onto the body, for example, to repair a burn or wound. This approach requires printers capable of adjusting parameters like pressure, temperature, and speed in real time – a task ideally suited for AI optimization.

Using the BioAssemblyBot 400, the researchers have been training machine-learning models on thousands of bioprinting experiments conducted under varying conditions. The system analyzes each print’s structure and consistency before automatically adjusting its settings for the next attempt. After more than a year of data collection, the team has compiled what is believed to be the largest dataset focused on print-quality optimization, consisting of over 2,000 prints.

The project, led by Distinguished University Professor and Fischell Department of Bioengineering Chair John Fisher, highlights how AI can accelerate and refine the bioprinting process. By dramatically reducing the time needed to determine optimal parameters, the technology brings the field closer to reliable, large-scale production of lab-grown tissues.

In the coming years, these advances could enable faster, more consistent fabrication of bioprinted materials for biomedical research and, eventually, clinical applications – a step toward a world where tissue repair and replacement are as immediate as pressing ‘print’.